IT-Software Engineer

Accord Technologies Inc; Chicago (IL); On-site; USD 96,000 - 165,000; Full time

Job summary

Accord Technologies Inc. in Chicago, IL seeks an IT-Software Engineer to design and orchestrate stateful AI systems and distributed backend services.

You will integrate foundation models via secure APIs, optimize data models for AI-native architectures, and ensure scalable, secure software across teams. The role requires 8+ years in software engineering, leadership experience, and deep knowledge of microservices, cloud-native practices, and AI tooling.

Qualifications

• Bachelor's degree in Computer Science or Electrical Engineering or related field.
• 8+ years of professional software engineering experience and 2+ years in a technical leadership role.
• Proven experience designing and delivering large-scale distributed systems.
• Strong expertise in software architecture, APIs, microservices, cloud-native applications, and modern engineering practices.
• Experience influencing multiple engineering teams and leading organization-wide technical initiatives.
• Strong communication, collaboration, and stakeholder management skills.
• Demonstrated ability to mentor engineers and drive technical excellence.
• Experience with Generative AI, AI agents, LLM-powered applications, or intelligent automation platforms.
• Experience with AI development tools, coding assistants, and modern developer productivity platforms.
• Knowledge of security architecture, application security, and cloud security best practices.
• Experience establishing technical governance and engineering standards across multiple teams.

Responsibilities

• Design and orchestrate multi-agent workflows and stateful AI systems using modern frameworks like LangChain, LangGraph, AutoGen, or CrewAI.
• Integrate foundation models via secure API gateways, managing token limits, costs, and rate-limiting.
• Architect data models optimized for AI-native structures, integrating relational databases with vector databases for semantic search and RAG.
• Implement robust white-box testing and continuous evaluation metrics to monitor AI outputs for factual correctness, hallucinations, and safety compliance.
• Champion secure, reliable, and scalable software solutions through architectural leadership, risk management, and continuous improvement of engineering practices.
• Mentor and scale an engineering team, establishing engineering standards, best practices and architectural governance for secure coding, CI/CD, and cloud-native deployment.
• Drive AI-assisted engineering velocity by integrating next-gen development tools into the SDLC.
• Establish governance policies and coach developers on responsible AI use, data sensitivity, and security guardrails.
• Evaluate existing systems, services, APIs, and data models to identify opportunities for modernization, scalability, and performance improvements.
• Facilitate technical leadership forums with Product Owners, Technical Leads, Architects, and Engineering Managers.
• Drive conversations around architecture, engineering health, technical debt, and AI adoption.
• Mentor engineers and technical leaders on system design, software architecture, and engineering excellence.
• Foster collaborative decision-making through architecture reviews, RFCs, and technical discussions.
• Promote self-service engineering capabilities and platform enablement.
• Drive automation initiatives that improve productivity and software quality.
• Significant interaction with Scrum ceremonies and PR reviews; collaboration with cross-team needs.

Skills

Distributed systems design

Software architecture

APIs & microservices

AI/LLM integration

Cloud & DevOps

Security & governance

Mentoring engineers

Team collaboration

Communication with stakeholders

Generative AI tooling

Education

Bachelor's degree in Computer Science or Electrical Engineering

Tools

Docker

Kubernetes

AWS

Job description

Job Title: IT-Software Engineer

Location : Chicago, IL

Type: W2 Contract

Required Education/Experience

• Bachelor s degree in Computer science or Electrical engineering or related field

Required Technical Skills

• 8+ years of professional software engineering experience and 2+ years in a technical leadership role.
• Proven experience designing and delivering large-scale distributed systems.
• Strong expertise in software architecture, APIs, microservices, cloud-native applications, and modern engineering practices.
• Experience influencing multiple engineering teams and leading organization-wide technical initiatives.
• Strong communication, collaboration, and stakeholder management skills.
• Demonstrated ability to mentor engineers and drive technical excellence.
• Experience with Generative AI, AI agents, LLM-powered applications, or intelligent automation platforms.
• Experience with AI development tools, coding assistants, and modern developer productivity platforms.
• Knowledge of security architecture, application security, and cloud security best practices.
• Experience establishing technical governance and engineering standards across multiple teams.

Required Soft Skills

• Ability to work under pressure and within time constraints
• Passion for technology and an eagerness to contribute to a team-oriented environment
• Lead architectural designs and able to work across teams to come up with solutions.

Summary Of Role

• Design and orchestrate multi-agent workflows and stateful AI systems using modern frameworks like LangChain, LangGraph, AutoGen, or CrewAI.
• Integrate foundation models (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) via secure API gateways, managing token limits, costs, and rate-limiting.
• Architect data models optimized for AI-native structures, integrating relational databases with vector databases for semantic search and Retrieval-Augmented Generation (RAG).
• Implement robust white-box testing and continuous evaluation metrics to monitor AI outputs for factual correctness, hallucinations, and safety compliance.
• Champion secure, reliable, and scalable software solutions through architectural leadership, risk management, and continuous improvement of engineering practices.

Technical Leadership & Workflow Optimization

• Mentor and scale an engineering team, establishing engineering standards, best practices and architectural governance for secure coding, continuous integration, and cloud-native deployment.
• Drive AI-assisted engineering velocity by integrating next-gen development tools (e.g., Cursor, Claude Code, Windsurf) into the team's daily Software Development Life Cycle (SDLC).
• Establish governance policies and coach developers on the responsible use of AI, focusing on input data sensitivity, license compliance, and security guardrails.
• Evaluate existing systems, services, APIs, and data models to identify opportunities for modernization, scalability, and performance improvements.

Influence Across Teams & Champion Developer Experience

• Facilitate technical leadership forums with Product Owners, Technical Leads, Architects, and Engineering Managers.
• Drive conversations around architecture, engineering health, technical debt, AI adoption, and continuous improvement.
• Mentor engineers and technical leaders on system design, software architecture, and engineering excellence.
• Foster collaborative decision-making through architecture reviews, RFCs, and technical discussions.
• Promote self-service engineering capabilities and platform enablement.
• Drive automation initiatives that improve productivity and software quality.

Interaction With Team

• Significant interaction required with Scrum team. Interaction during all scrum ceremonies such as Daily Standups, Sprint Planning, Grooming, Retro, Demo etc
• Also need to interact with team for PR Reviews, also need to engage with other teams as needed.

Core Software Engineering

• Backend Systems: Deep proficiency in backend environments, microservices architectures, and API design using Java.
• Cloud & DevOps: Extensive experience with containerization (Docker, Kubernetes) and public cloud infrastructure like AWS AI & LLM Infrastructure
• Orchestration & Tooling: Hands-on experience with production-level AI agents, prompt engineering, and advanced Agentic PDLC patterns.
• Vector Databases: Practical knowledge of vector technologies such as Pinecone, Milvus, Chroma, or pgvector.
• AI Tool Fluency: Demonstrated mastery of AI coding assistants and a firm understanding of Model Context Protocol (MCP) to mediate agent connections with external databases.